01235nas a2200145 4500008004100000245012400041210006900165300001100234490000600245520065800251653002200909100001700931700001900948856012200967 1988 eng d00aSPOT satellite data for pattern recognition on the North American tall-grass prairie Long-term Ecological Research Site0 aSPOT satellite data for pattern recognition on the North America a37 -400 v33 a

The cluster routine uses a two-pass sequential clustering algorithm. In the first pass, the program reads through the entire data set, and sequentially builds clusters (groups of points in spectral space) based on parameters selected by the user, and computes the mean value for each cluster. These clusters become the signatures used to assign classes in the output GIS file. The second pass classifies each pixel in the data set according to a minimum distance classifier. The algorithm calculates the spectral distance between the candidate pixel and the mean value for every cluster, using the mean values that were computed in the first pass